12 research outputs found
Low-risk susceptibility alleles in 40 human breast cancer cell lines
Background: Low-risk breast cancer susceptibility alleles or SNPs confer only modest breast cancer risks ranging from just over 1.0 to 1.3 fold. Yet, they are common among most populations and therefore are involved in the development of essentially all breast cancers. The mechanism by which the low-risk SNPs confer breast cancer risks is currently unclear. The breast cancer association consortium BCAC has hypothesized that the low-risk SNPs modulate expression levels of nearby located genes. Methods: Genotypes of five low-risk SNPs were determined for 40 human breast cancer cell lines, by direct sequencing of PCR-amplified genomic templates. We have analyzed expression of the four genes that are located nearby the low-risk SNPs, by using real-time RT-PCR and Human Exon microarrays. Results: The SNP genotypes and additional phenotypic data on the breast cancer cell lines are presented. We did not detect any effect of the SNP genotypes on expression levels of the nearby-located genes MAP3K1, FGFR2, TNRC9 and LSP1. Conclusion: The SNP genotypes provide a base line for functional studies in a well-characterized cohort of 40 human breast cancer cell lines. Our expression analyses suggest that a putative disease mechanism through gene expression modulation is not operative in breast cancer cell lines
CYP17 genetic polymorphism, breast cancer, and breast cancer risk factors: Australian Breast Cancer Family Study
INTRODUCTION: Because CYP17 can influence the degree of exposure of breast tissues to oestrogen, the interaction between polymorphisms in this gene and hormonal risk factors is of particular interest. We attempted to replicate the findings of studies assessing such interactions with the -34T→C polymorphism. METHODS: Risk factor and CYP17 genotyping data were derived from a large Australian population-based case-control-family study of 1,284 breast cancer cases and 679 controls. Crude and adjusted odds ratio (OR) estimates and 95% confidence intervals (CIs) were calculated by unconditional logistic regression analyses. RESULTS: We found no associations between the CYP17 genotype and breast cancer overall. Premenopausal controls with A(2)/A(2 )genotype had a later age at menarche (P < 0.01). The only associations near statistical significance were that postmenopausal women with A(1)/A(1 )(wild-type) genotype had an increased risk of breast cancer if they had ever used hormone replacement therapy (OR 2.40, 95% CI 1.0 to 5.7; P = 0.05) and if they had menopause after age 47 years (OR 2.59, 95% CI 1.0 to 7.0; P = 0.06). We found no associations in common with any other studies, and no evidence for interactions. CONCLUSION: We observed no evidence of effect modification of reproductive risk factors by CYP17 genotype, although the experiment did not have sufficient statistical power to detect small main effects and modest effects in subgroups. Associations found only in subgroup analyses based on relatively small numbers require cautious interpretation without confirmation by other studies. This emphasizes the need for replication in multiple and large population-based studies to provide convincing evidence for gene–environment interactions
Gene expression profiling assigns CHEK2 1100delC breast cancers to the luminal intrinsic subtypes
CHEK2 1100delC is a moderate-risk cancer susceptibility allele that confers a high breast cancer risk in a polygenic setting. Gene expression profiling of CHEK2 1100delC breast cancers may reveal clues to the nature of the polygenic CHEK2 model and its genes involved. Here, we report global gene expression profiles of a cohort of 155 familial breast cancers, including 26 CHEK2 1100delC mutant tumors. In line with previous work, all CHEK2 1100delC mutant tumors clustered among the hormone receptor-positive breast cancers. In the hormone receptor-positive subset, a 40-gene CHEK2 signature was subsequently defined that significantly associated with CHEK2 1100delC breast cancers. The identification of a CHEK2 gene signature implies an unexpected biological homogeneity among the CHEK2 1100delC breast cancers. In addition, all 26 CHEK2 1100delC tumors classified as luminal intrinsic subtype breast cancers, with 8 luminal A and 18 luminal B tumors. This biological make-up of CHEK2 1100delC breast cancers suggests that a relatively limited number of additional susceptibility alleles are involved in the polygenic CHEK2 model. Identification of these as-yet-unknown susceptibility alleles should be aided by clues from the 40-gene CHEK2 signatur